In recent years many successful machine learning applications have been developed, ranging from datamining
programs to information-filtering systems that learn users' reading preferences. At the same time, there have
been important advances in the theory and algorithms that can be used identify the diseases and treatment relations
in a Bio-Science text. Imagine a computer learns from medical records which treatments are most effective for new
diseases. Having the machine learning concept behind we have proposed a Machine Learning (ML) approach based
on Na´ve Bayes (NB) algorithm to improve the automatic disease identification in the medical field. And also we
have improved text classification by using an integrated model.